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Single Cell Genomics Reveals Plastid-Lacking Picozoa Are Close Relatives of Red Algae

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Supplementary Information for Single cell genomics reveals plastid-lacking Picozoa are close relatives of red algae Max E. Schön, Vasily V. Zlatogursky, Rohan P. Singh, Camille Poirier, Susanne Wilken, Varsha Mathur, Jürgen F. H. Strassert, Jarone Pinhassi, Alexandra Z. Worden, Patrick J. Keeling, Thijs J. G. Ettema, Jeremy G. Wideman, Fabien Burki* List of Figures 1 Maximum Likelihood tree of the 18S rRNA gene. ........................... 3 2 Combined relative abundance of all Picozoa OTUs identified in the Tara Oceans metabarcoding data. .................................................... 4 3 Maximum likelihood tree of 794 eukaryotic species. .......................... 5 4 Support for several groupings as estimated in different trees with increasing number of fast- evolving sites removed. ......................................... 6 5 Maximum likelihood tree of 67 eukaryotic species showing the position of Picozoa. 6 6 Multi-species coalescent species tree reconstructed with ASTRAL-III. ............... 7 7 Maximum likelihood tree of 67 eukaryotic species showing the position of Picozoa. 8 8 Maximum likelihood tree of 67 eukaryotic species showing the position of Picozoa. 9 9 Complete and near complete mitochondrial genomes assembled from diverse picozoan SAGs. 10 10 Number of inferred lateral gene transfers (LGT) across a selection of 33 species. ......... 11 11 Maximum Likelihood tree of the 18S rRNA gene from the individual SAG assemblies and an extended number of reference sequences from Picozoa and other major eukaryotic groups from the PR2 database. ............................................ 12 12 Heatmap showing pairwise ANI for 43 initial picozoan SAGs as estimated with FastANI. 13 13 Boxplots of different BUSCO categories (Missing, Complete, Fragmented and Duplicated) for all selected SAGs/Co-SAGs. ........................................ 13 14 Contamination estimate for each of the 17 final SAGs/Co-SAGs. 14 15 Maximum likelihood tree of eukaryotic species showing the position of Picozoa. 15 16 Bayesian phylogenetic tree made using PhyloBayes. ......................... 16 17 Bayesian phylogenetic tree made using PhyloBayes. ......................... 17 List of Tables 1 Assembly/genome characteristics SAGs and CO-SAGs ....................... 18 1 2 Additional genomes added to the Phylogenomic dataset ....................... 18 3 Phylogenomic dataset taxon selection and taxon merging ...................... 18 4 Results from the AU and other topology tests performed with IQ-TREE . 18 5 The Picozoan MS584-11 mitochondrial genome was used as a BLAST query into the 43 picozoan SAGs. ................................................... 18 6 Commonly retained plastid pathways and proteins .......................... 18 7 EGT clustering dataset taxon selection ................................. 18 8 Phylogenomic dataset taxon selection and taxon merging ...................... 18 9 EGT and LGT results for 33 selected species/groups ......................... 18 1 untrimmed EEF2 alignment ....................................... 18 2 3 0 SAG17_NODE_209_length_6604_cov_12.631822_939-2744 2 7 'BP1' 3 0 SAG41_NODE_729_length_1138_cov_22.611165_1-553 9 SAG09_NODE_597_length_2008_cov_1.544264_102-784 SAG43_NODE_6386_length_1046_cov_569.933474_20-1046 3 2 SAG16_NODE_467_length_2239_cov_20.097664_535-2239 6 5 JX988764.1.1138_U_clone_PICOBI01F-L52R_10 4 9 1 2 KJ763213.1.1806_U_clone_SGUH612 COSAG02 SAG41_NODE_563_length_1533_cov_4.731520_304-1533 2 0 SAG35_NODE_69_length_11959_cov_32.509528_8945-10750 2 79 SAG21_NODE_816_length_2079_cov_2.398990_290-2079 6 5 SAG32_NODE_791_length_6633_cov_1359.747626_737-2542 SAG18_NODE_1586_length_1284_cov_1.328270_750-1215 8 SAG34_NODE_220_length_626_cov_0.867173_100-625 6 7 EU368003.1.1109_U_clone_FS01AA11_01Aug05_5m 9 5 EU368004.1.1126_U_clone_FS01AA94_01Aug05_5m 24 3 5 EU368020.1.1039_U_clone_FS04GA95_01Aug05_5m 100 DQ222876.1.1799_U_clone_RA000907.33 4 2 JF791041.1.1777_U_clone_7532 SAG18_NODE_3756_length_534_cov_0.671264_2-533 8 9 JX988758.1.1807_U_Picomonas_judraskeda 5 2 8 0 SAG01_NODE_1281_length_3345_cov_9.888478_301-2106 4 1 HQ867389.1.887_U_clone_SHAC701 COSAG03 SAG40_NODE_1486_length_1870_cov_3.223602_876-1870 4 5 SAG02_NODE_164_length_1182_cov_0.938135_1-1175 100 HQ869261.1.1000_U_clone_SHBA597 4 5 4 8 HQ869362.1.935_U_clone_SHBA707 41 73 SAG09_NODE_2410_length_432_cov_0.936937_1-430 KC488338.1.1714_U_clone_HL2SCM10.71 3 8 SAG36_NODE_269_length_5276_cov_1081.533127_3-1607 SAG26_NODE_716_length_5622_cov_237.617237_668-2473 6 5 SAG39_NODE_1105_length_5866_cov_172.926131_882-2687 COSAG06 5 8 SAG30_NODE_204_length_11251_cov_42.867737_1433-3238 7 9 SAG27_NODE_219_length_12917_cov_16.477298_7670-9475 5 3 JN934893.1_Picobiliphyte_SAG_sp._MS609-66 7 8 JN934890.1_Picobiliphyte_SAG_MS584-5 KJ762479.1.1805_U_clone_SGYH1057 JQ226352.1.1606_U_clone_SHAA389 3 6 4 3 KF031848.1.1765_U_clone_CC02A175.091 8 0 KJ173845.1.986_U_clone_DH117-1000m-C02 7 9100 SAG23_NODE_141_length_11148_cov_11.089963_3919-5724 COSAG04 SAG19_NODE_794_length_9268_cov_1638.280401_2687-4492 KJ173847.1.992_U_clone_DH117-1000m-C10 6 7 HQ868776.1.919_U_clone_SHAX1019 100 7 7 HQ868797.1.923_U_clone_SHAX1043 7 4 HQ868690.1.947_U_clone_SHAX927 4 0 KJ759275.1.1806_U_clone_SGYO1039 7 1 SAG08_NODE_2796_length_1578_cov_105.795132_5-1572 3 1 SAG42_NODE_33_length_26034_cov_34.003856_573-2378 SAG29_NODE_208_length_10399_cov_14.269126_3742-5547 7 0 SAG13_NODE_154_length_12455_cov_60.081013_5953-7758 COSAG01 8 4 SAG04_NODE_206_length_16512_cov_7.695729_11513-13318 6 1 9 9 SAG24_NODE_30_length_15199_cov_8.991656_4494-6299 9 0 SAG20_NODE_95_length_11004_cov_58.023107_5150-6955 SAG12_NODE_286_length_10619_cov_339.861977_9641-10619 KJ762972.1.1807_U_clone_SGUH1326 5 3 HQ869099.1.906_U_clone_SHAX616 4 5 6 3 100 HQ869574.1.909_U_clone_SHBF544 4 1 HQ869605.1.957_U_clone_SHBF578 6 1 HQ869692.1.905_U_clone_SHBF671 9 9 KC488345.1.1706_U_clone_HL5aSF04.93 JQ222911.1.1637_U_clone_SHAU435 6 6 HM561168.1.984_U_clone_CFL146DB13 3 8 SAG38_NODE_1157_length_2077_cov_56.130515_304-2077 7 2 3 8 SAG14_NODE_6_length_54255_cov_1799.083795_52455-54255 8 1 SAG06_NODE_69_length_968_cov_0.676640_12-968 SAG06_NODE_305_length_411_cov_0.810897_3-411 6 6 9 8 EU368037.1.1764_U_clone_EN351CTD039_30mN9 COSAG05 8 3 9 9 JN934891.1_Picobiliphyte_SAG_sp._MS584-11 'BP3' SAG15_NODE_683_length_4737_cov_2550.787193_738-2541 7 1 KJ173846.1.991_U_clone_DH117-1000m-C07 KJ173838.1.862_U_clone_DH113-5m-D02 100 DQ222875.1.1801_U_clone_OR000415.159 6 7 100 JN934892.1_Picobiliphyte_SAG_sp._MS584-22 HQ867491.1.910_U_clone_SHAH476 9 9 HQ867421.1.875_U_clone_SHAC745 7 1 8 1 KF130491.1.1763_U_clone_ST8360.104 SAG22_NODE_175_length_16235_cov_67.112729_1670-3473 8 5 9 8 DQ222874.1.1786_U_clone_HE001005.148 JX988767.1.1135_U_clone_PICOBI02F-L52R_He 9 9 EU368021.1.1096_U_clone_FS04GA46_01Aug05_5m 100 9 3 AY426835.1.1803_U_clone_BL000921.8 SAG31_NODE_544_length_14245_cov_68.376644_6887-8690 'BP2' 8 0 HQ869075.1.930_U_clone_SHAX587 8 2 100 100 JX840937.1.1271_U_clone_ARK_21 KJ173843.1.991_U_clone_DH116-100m-C03 'Deep branching Picozoa 1' KJ173850.1.854_U_clone_DH117-1000m-D03 7 4 100 KJ763562.1.1796_U_clone_SGYP1354 SAG11_NODE_229_length_11945_cov_77.865187_857-2654 8 9 6 0 DQ060528.1.800_U_clone_NOR50.25 100 DQ060527.1.1237_U_clone_NOR50.52 9 2 KC488340.1.1697_U_clone_HL5aSCM04.10 9 8 HM561172.1.953_U_clone_CFL119DB12 8 8 6 6 KJ762470.1.1800_U_clone_SGYH1041 'Deep branching Picozoa 2' 100 KC488342.1.1710_U_clone_HL5aSCM04.38 HQ868882.1.878_U_clone_SHAX1135 KC488336.1.1682_U_clone_BBL1SF10.02 9 9 HQ867420.1.880_U_clone_SHAC744 5 7 8 6 HQ867337.1.876_U_clone_SHAC623 5 0 HQ867471.1.868_U_clone_SHAC426 4 6 8 9 AY343928.1.1812_U_clone_He000803-72 2 2 KJ759623.1.1791_U_clone_SGYO702 KC488339.1.1675_U_clone_HL2SF10.08 5 6 GU824414.1.1057_U_clone_AA5F13RM2D10 7 5 100 HQ867331.1.869_U_clone_SHAC614 4 7 HQ867442.1.871_U_clone_SHAC390 3 5 DQ060524.1.1778_U_clone_NW414.27 SAG28_NODE_1308_length_928_cov_36.342746_1-913 7 1 HQ866220.1.881_U_clone_SGSP644 8 1 7 3 HQ869572.1.881_U_clone_SHBF542 KC488334.1.1687_U_clone_BBL1SCM04.08 9 9 100 EU561759.1.879_U_clone_IND31.88 KJ759641.1.1788_U_clone_SGYO733 HQ867427.1.876_U_clone_SHAC752 8 9 FN689854.1.826_U_clone_He040503_11A HQ864893.1.880_U_clone_SGPX462 100 U53126.1.1756_U_strain_CCMP_325_Eukaryota_Hacrobia_Cryptophyta_Cryptophyceae_Cryptomonadales_Cryptomonadales_X_Hanusia_Hanusia_phi 6 9 4 3 X57162.1.1773_U__Eukaryota_Hacrobia_Cryptophyta_Cryptophyceae_Cryptomonadales_Cryptomonadales_X_Guillardia_Guillardia_theta 7 2 L28811.1.1763_U_strain_CCAP_977_2a_Eukaryota_Hacrobia_Cryptophyta_Cryptophyceae_Cryptomonadales_Cryptomonadales_X_Cryptomonas_Cryptomonas_paramecium 9 2 HM126532.1.1732_U_strain_K-1487_Eukaryota_Hacrobia_Cryptophyta_Cryptophyceae_Cryptomonadales_Cryptomonadales_X_Rhodomonas_Rhodomonas_salina 8 3 AJ007285.1.1761_U_strain_CCMP_704_Eukaryota_Hacrobia_Cryptophyta_Cryptophyceae_Cryptomonadales_Cryptomonadales_X_Proteomonas_Proteomonas_sulcata 9 7 AM901350.1.1670_U_strain_CCMP_441_Eukaryota_Hacrobia_Cryptophyta_Cryptophyceae_Cryptomonadales_Cryptomonadales_X_Hemiselmis_Hemiselmis_andersenii JF790986.1.1777_U_clone_1126_Eukaryota_Hacrobia_Cryptophyta_Cryptophyceae_Cryptomonadales_Cryptomonadales_X_Geminigera_Geminigera_cryophila AF508277.1.1721_U_strain_CCMP1869_Eukaryota_Hacrobia_Cryptophyta_Cryptophyceae_Goniomonadales_Goniomonadales_X_Goniomonas_Goniomonas_pacifica 100 HQ191366.1.1830_U_clone_PA2009C5_Eukaryota_Hacrobia_Katablepharidophyta_Katablepharidaceae_Katablepharidales_Katablepharidales_X_Katablepharidales_XX_Katablepharidales_XX_sp. 9 9 2 7 GU068005.1.1774_U_clone_ESS241006.012_Eukaryota_Hacrobia_Katablepharidophyta_Katablepharidaceae_Katablepharidales_Katablepharidales_X_Katablepharidales_XX_Katablepharidales_XX_sp.
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  • Chemical Composition and Potential Practical Application of 15 Red Algal Species from the White Sea Coast (The Arctic Ocean)

    Chemical Composition and Potential Practical Application of 15 Red Algal Species from the White Sea Coast (The Arctic Ocean)

    molecules Article Chemical Composition and Potential Practical Application of 15 Red Algal Species from the White Sea Coast (the Arctic Ocean) Nikolay Yanshin 1, Aleksandra Kushnareva 2, Valeriia Lemesheva 1, Claudia Birkemeyer 3 and Elena Tarakhovskaya 1,4,* 1 Department of Plant Physiology and Biochemistry, Faculty of Biology, St. Petersburg State University, 199034 St. Petersburg, Russia; [email protected] (N.Y.); [email protected] (V.L.) 2 N. I. Vavilov Research Institute of Plant Industry, 190000 St. Petersburg, Russia; [email protected] 3 Faculty of Chemistry and Mineralogy, University of Leipzig, 04103 Leipzig, Germany; [email protected] 4 Vavilov Institute of General Genetics RAS, St. Petersburg Branch, 199034 St. Petersburg, Russia * Correspondence: [email protected] Abstract: Though numerous valuable compounds from red algae already experience high demand in medicine, nutrition, and different branches of industry, these organisms are still recognized as an underexploited resource. This study provides a comprehensive characterization of the chemical composition of 15 Arctic red algal species from the perspective of their practical relevance in medicine and the food industry. We show that several virtually unstudied species may be regarded as promis- ing sources of different valuable metabolites and minerals. Thus, several filamentous ceramialean algae (Ceramium virgatum, Polysiphonia stricta, Savoiea arctica) had total protein content of 20–32% of dry weight, which is comparable to or higher than that of already commercially exploited species Citation: Yanshin, N.; Kushnareva, (Palmaria palmata, Porphyra sp.). Moreover, ceramialean algae contained high amounts of pigments, A.; Lemesheva, V.; Birkemeyer, C.; macronutrients, and ascorbic acid. Euthora cristata (Gigartinales) accumulated free essential amino Tarakhovskaya, E.
  • Coccolithophore Distribution in the Mediterranean Sea and Relate A

    Coccolithophore Distribution in the Mediterranean Sea and Relate A

    Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Ocean Sci. Discuss., 11, 613–653, 2014 Open Access www.ocean-sci-discuss.net/11/613/2014/ Ocean Science OSD doi:10.5194/osd-11-613-2014 Discussions © Author(s) 2014. CC Attribution 3.0 License. 11, 613–653, 2014 This discussion paper is/has been under review for the journal Ocean Science (OS). Coccolithophore Please refer to the corresponding final paper in OS if available. distribution in the Mediterranean Sea Is coccolithophore distribution in the A. M. Oviedo et al. Mediterranean Sea related to seawater carbonate chemistry? Title Page Abstract Introduction A. M. Oviedo1, P. Ziveri1,2, M. Álvarez3, and T. Tanhua4 Conclusions References 1Institute of Environmental Science and Technology (ICTA), Universitat Autonoma de Barcelona (UAB), 08193 Bellaterra, Spain Tables Figures 2Earth & Climate Cluster, Department of Earth Sciences, FALW, Vrije Universiteit Amsterdam, FALW, HV1081 Amsterdam, the Netherlands J I 3IEO – Instituto Espanol de Oceanografia, Apd. 130, A Coruna, 15001, Spain 4GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel, Marine Biogeochemistry, J I Duesternbrooker Weg 20, 24105 Kiel, Germany Back Close Received: 31 December 2013 – Accepted: 15 January 2014 – Published: 20 February 2014 Full Screen / Esc Correspondence to: A. M. Oviedo ([email protected]) Published by Copernicus Publications on behalf of the European Geosciences Union. Printer-friendly Version Interactive Discussion 613 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Abstract OSD The Mediterranean Sea is considered a “hot-spot” for climate change, being char- acterized by oligotrophic to ultra-oligotrophic waters and rapidly changing carbonate 11, 613–653, 2014 chemistry. Coccolithophores are considered a dominant phytoplankton group in these 5 waters.
  • Download PDF Version

    Download PDF Version

    MarLIN Marine Information Network Information on the species and habitats around the coasts and sea of the British Isles A red seaweed (Furcellaria lumbricalis) MarLIN – Marine Life Information Network Biology and Sensitivity Key Information Review Will Rayment 2008-05-22 A report from: The Marine Life Information Network, Marine Biological Association of the United Kingdom. Please note. This MarESA report is a dated version of the online review. Please refer to the website for the most up-to-date version [https://www.marlin.ac.uk/species/detail/1616]. All terms and the MarESA methodology are outlined on the website (https://www.marlin.ac.uk) This review can be cited as: Rayment, W.J. 2008. Furcellaria lumbricalis A red seaweed. In Tyler-Walters H. and Hiscock K. (eds) Marine Life Information Network: Biology and Sensitivity Key Information Reviews, [on-line]. Plymouth: Marine Biological Association of the United Kingdom. DOI https://dx.doi.org/10.17031/marlinsp.1616.2 The information (TEXT ONLY) provided by the Marine Life Information Network (MarLIN) is licensed under a Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales License. Note that images and other media featured on this page are each governed by their own terms and conditions and they may or may not be available for reuse. Permissions beyond the scope of this license are available here. Based on a work at www.marlin.ac.uk (page left blank) Date: 2008-05-22 A red seaweed (Furcellaria lumbricalis) - Marine Life Information Network See online review for distribution map The seaweed Furcellaria lumbricalis, plant with fertile branches.
  • Fig.S1. the Pairwise Aligments of High Scoring Pairs of Recognizable Pseudogenes

    Fig.S1. the Pairwise Aligments of High Scoring Pairs of Recognizable Pseudogenes

    LysR transcriptional regulator Identities = 57/164 (35%), Positives = 82/164 (50%), Gaps = 13/164 (8%) 70530- SNQAIKTYLMPK*LRLLRQK*SPVEFQLQVHLIKKIRLNIVIRDINLTIIEN-TPVKLKI -70354 ++Q TYLMP+ + L RQK V QLQVH ++I ++ INL II P++LK 86251- ASQTTGTYLMPRLIGLFRQKYPQVAVQLQVHSTRRIAWSVANGHINLAIIGGEVPIELKN -86072 70353- FYTLLRMKERI*H*YCLGFL------FQFLIAYKKKNLYGLRLIKVDIPFPIRGIMNNP* -70192 + E L + F L + +K++LY LR I +D IR +++ 86071- MLQVTSYAED-----ELALILPKSHPFSMLRSIQKEDLYRLRFIALDRQSTIRKVIDKVL -85907 70191- IKTELIPRNLN-EMELSLFKPIKNAV*PGLNVTLIFVSAIAKEL -70063 + + EMEL+ + IKNAV GL + VSAIAKEL 85906- NQNGIDSTRFKIEMELNSVEAIKNAVQSGLGAAFVSVSAIAKEL -85775 ycf3 Photosystem I assembly protein Identities = 25/59 (42%), Positives = 39/59 (66%), Gaps = 3/59 (5%) 19162- NRSYML-SIQCM-PNNSDYVNTLKHCR*ALDLSSKL-LAIRNVTISYYCQDIIFSEKKD -19329 +RSY+L +I + +N +YV L++ ALDL+S+L AI N+ + Y+ Q + SEKKD 19583- DRSYILYNIGLIYASNGEYVKALEYYHQALDLNSRLPPAINNIAVIYHYQGVKASEKKD -19759 Fig.S1. The pairwise aligments of high scoring pairs of recognizable pseudogenes. The upper amino acid sequences indicates Cryptomonas sp. SAG977-2f. The lower sequences are corresponding amino acid sequences of homologs in C. curvata CCAP979/52. Table S1. Presence/absence of protein genes in the plastid genomes of Cryptomonas and representative species of Cryptomonadales. Note; y indicates pseudogenes. Photosynthetic Non-Photosynthetic Guillardia Rhodomonas Cryptomonas C. C. curvata C. curvata parameciu Guillardia Rhodomonas FBCC300 CCAP979/ SAG977 CCAC1634 m theta salina -2f B 012D 52 CCAP977/2 a rps2 + + + +
  • Lateral Gene Transfer of Anion-Conducting Channelrhodopsins Between Green Algae and Giant Viruses

    Lateral Gene Transfer of Anion-Conducting Channelrhodopsins Between Green Algae and Giant Viruses

    bioRxiv preprint doi: https://doi.org/10.1101/2020.04.15.042127; this version posted April 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 5 Lateral gene transfer of anion-conducting channelrhodopsins between green algae and giant viruses Andrey Rozenberg 1,5, Johannes Oppermann 2,5, Jonas Wietek 2,3, Rodrigo Gaston Fernandez Lahore 2, Ruth-Anne Sandaa 4, Gunnar Bratbak 4, Peter Hegemann 2,6, and Oded 10 Béjà 1,6 1Faculty of Biology, Technion - Israel Institute of Technology, Haifa 32000, Israel. 2Institute for Biology, Experimental Biophysics, Humboldt-Universität zu Berlin, Invalidenstraße 42, Berlin 10115, Germany. 3Present address: Department of Neurobiology, Weizmann 15 Institute of Science, Rehovot 7610001, Israel. 4Department of Biological Sciences, University of Bergen, N-5020 Bergen, Norway. 5These authors contributed equally: Andrey Rozenberg, Johannes Oppermann. 6These authors jointly supervised this work: Peter Hegemann, Oded Béjà. e-mail: [email protected] ; [email protected] 20 ABSTRACT Channelrhodopsins (ChRs) are algal light-gated ion channels widely used as optogenetic tools for manipulating neuronal activity 1,2. Four ChR families are currently known. Green algal 3–5 and cryptophyte 6 cation-conducting ChRs (CCRs), cryptophyte anion-conducting ChRs (ACRs) 7, and the MerMAID ChRs 8. Here we 25 report the discovery of a new family of phylogenetically distinct ChRs encoded by marine giant viruses and acquired from their unicellular green algal prasinophyte hosts.